Uber is turning data about trips and takeout into insights for marketers

Privacy, “Anonymization,” and Trust

• Many see this as confirmation that Uber will “go to any depth” to monetize users, not a new direction. Several are surprised it wasn’t already openly happening.
• Debate centers on whether aggregated / anonymized data is meaningfully safer than individual-level data.
  • One side: properly aggregated data is vastly less harmful than full profiles; equating them is a false equivalence.
  • Other side: “when done properly” is doing heavy lifting; real-world deanonymization of mobility datasets is common and often trivial when cross-referenced with other sources.
• Uber’s “clean room” arrangement is viewed skeptically; posters expect any privacy–utility tradeoff to be resolved in favor of advertisers, not users.

Advertising, Paid Services, and Being “the Product”

• Strong sentiment that paying does not stop companies from monetizing behavior; users of Prime, Crave, Uber, etc. report paying and still getting ads and data exploitation.
• Discussion over whether people actually care about data monetization:
  • Some argue most users object to ads mainly because they’re annoying, not because of tracking.
  • Others say people would care if they understood the implications, but are underinformed and see little credible way to buy privacy.
• “Vote with your wallet” is challenged: in markets where Uber has quasi-monopoly power, opting out is seen as impractical or symbolic.

Economics of Ads and Targeting

• Commenters note that users who pay to remove ads self-identify as high-disposable-income, making them more valuable to advertisers.
• Some ad-tech and marketing perspectives are shared: platforms price ads differently by device, audience, and context; premium, hard-to-reach segments are especially prized.

Personalization vs. Exploitation

• A minority explicitly want better, more personalized in-app suggestions (e.g., restaurants) and are willing to trade some data for convenience.
• Others argue “good recommendations” are really those that maximize advertiser revenue, not user welfare, and fear mobility data being used for behavioral prediction, price discrimination, or even political surveillance.

Alternatives, Regulation, and Public Use of Data

• Some vow to switch to taxis, local car services, or competitors like Waymo; others suggest piracy and self-hosted media as the only real escape from ad-driven models.
• Calls for stronger regulation: treating personal data as property requiring explicit, compensated, opt-in consent; skepticism about both libertarian “markets will fix it” and naive “regulation will fix it” views.
• A few propose mandating (properly anonymized) ride data sharing with local governments for transit planning, but others question both anonymization feasibility and government capacity to use it.